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Explore the intriguing world of adversarial examples in deep learning through this comprehensive lecture by Sébastien Bubeck from Microsoft Research. Delve into the surprising facts and challenges surrounding adversarial examples, and gain insights into the Statistical Learning Theory (SLT) framework. Discover the implications of the XPRIZE competition, examine various loss classes, and understand the concepts of VC dimension and complexity in the context of deep learning. This in-depth talk, presented as part of the Deep Learning Boot Camp at the Simons Institute, offers a thorough exploration of the subject matter for those interested in the cutting-edge developments in machine learning and artificial intelligence.
Syllabus
Introduction
Objective
Surprising Fact
The Talk
SLT Framework
XPRIZE
Loss classes
VC dimension
Complexity
Taught by
Simons Institute